Metadata-Version: 2.1
Name: pyglyph
Version: 0.5.1
Summary: Symbolic regression tools.
Home-page: https://github.com/Ambrosys/glyph
Author: Markus Abel, Julien Gout, Markus Quade
Author-email: markus.quade@ambrosys.de
License: LGPL
Description: glyph - symbolic regression tools
        =================================
        
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        **glyph** is a python 3 library based on deap providing abstraction
        layers for symbolic regression problems.
        
        It comes with batteries included:
        
        - predefined primitive sets
        - n-dimensional expression tree class
        - symbolic and structure-based constants
        - interfacing constant optimization to `scipy.optimize`
        - easy integration with `joblib` or `dask.distributed`
        - symbolic constraints
        - boilerplate code for logging, checkpointing, break conditions and command line applications
        - rich set of algorithms
        
        glyph also includes a plug and play command line application
        **glyph-remote** which lets non-domain experts apply symbolic regression
        to their optimization tasks.
        
        Installation
        ------------
        
        Glyph is a **python 3.6+** only package.
        
        You can install the latest stable version from PyPI with pip
        
        `pip install pyglyph`
        
        or get the bleeding edge
        
        `pip install git+git://github.com/ambrosys/glyph.git#egg=glyph`
        
        Documentation
        -------------
        
        The online documentation is available at
        [glyph.readthedocs.io](https://glyph.readthedocs.io).
        
        Bugs, feature requests, contributions
        -------------------------------------
        
        Please use the [issue tracker](https://github.com/Ambrosys/glyph/issues).
        For contributions have a look at out [contribution
        guide](https://github.com/ambrosys/glyph/blob/master/.github/CONTRIBUTING).
        
Keywords: complex systems,control,machine learning,genetic programming
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: License :: OSI Approved :: GNU Library or Lesser General Public License (LGPL)
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Provides-Extra: gui
